Both classes cna be used independently, if desired. An emphasis was placed on documentationĪnd easability of use. There are exisitng Python and Java modules for network scanning and RSSI-localization, but there was a need forĪ more extensive package that scales for a virtually unlimited number of Wifi access points. 'RSSI-based Algorithm for Indoor Localization' paper, published here: The algorithm used in this module is entirely base off of Xiuyan Zhu's, Yuan Feng's thisĬlass can not be used, without the use of three or more known accesspoints. RSSI_Localizer is used for self-localization, using the information returned by RSSI_Scan. RSSI_Scan is used to find and return information on all available access points, within range.Ī 'networks' list can be provided as an argument to filter networks of interest. This module contains two classes, 'RSSI_Scan' and 'RSSI_Localizer'. Locations are fixed, but modifications acn be made for moving access points). Known WIFI hotspots’ positions, it would be relatively easy to realize self-localization (Usually WIFI access points Of WIFI access point in buildings is increasing, as long as a mobile smart device can detect three or more With the development of wireless are networks and smart devices, the number Of access points, where 'n' >= 3 access points. RSSI-based localiztion algortihms require 'n' number RSSI (relative received signal strength) of nearby access-points (wifi routers). RSSI-based localization offers the ability to find an unknown position using the With IoT projects at an all time high, there is a continuous need for positioning and localization systems in places where
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